David Duvenaud
Publications by Year
Research Areas
Gaussian Processes and Bayesian Inference, Generative Adversarial Networks and Image Synthesis, Model Reduction and Neural Networks, Adversarial Robustness in Machine Learning, Neural Networks and Applications
Most-Cited Works
- → Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules.(2018)1,970 cited
- → Design of efficient molecular organic light-emitting diodes by a high-throughput virtual screening and experimental approach(2016)1,101 cited
- → Convolutional Networks on Graphs for Learning Molecular Fingerprints(2015)905 cited
- → Neural Ordinary Differential Equations(2018)566 cited
- → Automatic model construction with Gaussian processes(2014)514 cited
- → Gradient-based Hyperparameter Optimization through Reversible Learning(2015)403 cited
- → FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative\n Models(2018)320 cited
- → Structure Discovery in Nonparametric Regression through Compositional Kernel Search(2013)274 cited
- Latent Ordinary Differential Equations for Irregularly-Sampled Time Series(2019)
- → Composing graphical models with neural networks for structured representations and fast inference(2016)232 cited